Overview

Column

Confirmed Cases vs Deaths by countries

Date vs Vaccinated by countries

Ratio of Covishield and Covaxin

Column

Death ratio by Age

Comfirmed vs Deaths by Filtering Countries

Column

valuebox 1

Hiten Hemnani

Column

Shrayansh Agrawal

Column

Taher Nawab

Data Table

Covid-19 Raw data table

---
title: "Analysis of Covid-19"
output: 
  flexdashboard::flex_dashboard:
    theme:
      version: 4
      bg: "#101010"
      fg: "#FDF7F7" 
      primary: "#ED79F9"
      navbar-bg: "#3ADAC6"
      base_font: 
        google: Prompt
      heading_font:
        google: Sen
    orientation: columns
    vertical_layout: fill
    social: ["twitter","facebook","linkedin","menu"]
    source_code: embed
    navbar:
      - { icon: "fa-info-circle", title: "About", href: "#team" }
---

```{r setup, include=FALSE}
library(flexdashboard)
library(ggplot2)
library(readr)
library(plotly)
library(dplyr)
library(tidyr)
library(DT)
library(tidyverse)
setwd("C:/Users/hiten/OneDrive/Desktop/MAIN/PERSONAL/Programming  in R/dashboard")
```

# Overview

Column {.tabset .tabset-fade data-width=600}
-----------------------------------------------------------------------
### Confirmed Cases vs Deaths by countries

```{r}
covid_19<-read.csv("Corrected_Monthly_COVID19_Data.csv")
plot_ly(data=covid_19,x=~Confirmed,y=~Deaths,z=~Country,type = "scatter3d",mode="markers",frame=~Date)
```

### Date vs Vaccinated by countries
```{r}
plot_ly(data=covid_19,x=~Date,y=~Vaccinated,type = "scatter",mode="lines",hovertemplate="Date: %{x} <br> Vaccinated: %{y}",
        transforms = list(
          list(
            type = "filter",
            target = ~Country,
            operation = "=",
            value = 'USA'
          )
        ))%>%
  layout(
    updatemenus = list(
      list(
        buttons = lapply(unique(covid_19$Country),function(cat){
          list(method = "restyle",
               args = list("transforms[0].value", cat),
               label = cat)
          
        }),
        direction = "down"
      )
    )
  )
```

### Ratio of Covishield and Covaxin

```{r}
covid_long <- covid_19 %>%
  pivot_longer(cols = c(Covishield, Covaxin),
               names_to = "Vaccine",
               values_to = "Count")

plot_ly(data = covid_long,
        labels = ~Vaccine,
        values = ~Count,
        type = "pie",
        frame = ~Date,
        marker = list(colors = c("#3d5a80","#98c1d9")),
        transforms = list(
          list(
            type = "filter",
            target = ~Country,
            operation = "=",
            value = 'USA'
          )
        )) %>%
  layout(
    updatemenus = list(
      list(
        buttons = lapply(unique(covid_long$Country), function(country) {
          list(
            method = "restyle",
            args = list("transforms[0].value", country),
            label = country
          )
        }),
        direction = "down",
        showactive = TRUE
     )
    )
  )
```
Column {data-width=400}
-----------------------------------------------------------------------

### Death ratio by Age

```{r}
covid_death<-covid_19 %>%
  pivot_longer(cols=c(Deaths_0_17,Deaths_18_44,Deaths_45_60,Deaths_60_plus),
               names_to="Death",
               values_to = "Counts")

plot_ly(data = covid_death,
        labels = ~Death,
        values = ~Counts,
        type = "pie",
        frame = ~Date)
```

### Comfirmed vs Deaths by Filtering Countries

```{r}
plot_ly(data=covid_19,x=~Confirmed,y=~Deaths,type = "scatter",mode="markers",color = ~Date,
        transforms = list(
          list(
            type = "filter",
            target = ~Country,
            operation = "=",
            value = 'USA'
          )
        ))%>%
  layout(
    updatemenus = list(
      list(
        buttons = lapply(unique(covid_19$Country),function(cat){
          list(method = "restyle",
               args = list("transforms[0].value", cat),
               label = cat)
          
        }),
        direction = "down"
      )
    )
  )
```

#  {#team}

Column {data-width=300}
---

### valuebox 1

```{r}
  valueBox(
    value = "Hiten Hemnani",
    caption = "Developer",
    icon = "fa-user",
    color = "purple"
  )
```

Column {data-width=300}
---
###
  
```{r}
  valueBox(
    value = "Shrayansh Agrawal",
    caption = "Data Analyst",
    icon = "fa-user",
    color = "info"
  )
```
  
  Column {data-width=300}
---

###  

```{r}
  valueBox(
    value = "Taher Nawab",
    caption = "UI/UX Designer",
    icon = "fa-user",
    color = "primary"
  )
```

# Data Table

### Covid-19 Raw data table

```{r}
datatable(covid_19, 
          options = list(pageLength = 10, autoWidth = TRUE),
          filter = 'top',
          rownames = FALSE)
```